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About our client:
A fast-growing US-based company specializing in AI automation, powered by a small but dynamic team that thrives on innovation and rapid experimentation. They partner with companies they truly believe in, pushing boundaries to create cutting-edge interfaces and transformative experiences. By leveraging state-of-the-art AI, they craft emotionally engaging interactions and streamline business process automation—always staying ahead of the curve.
We are seeking a highly skilled AI Automation Engineer to design, develop, and deploy AI-driven automation workflows in enterprise environments. This role combines AI model engineering with enterprise automation, focusing on fine-tuning cloud-based AI models, optimizing retrieval-augmented generation (RAG) databases, and integrating structured automation workflows. The ideal candidate will have experience working with cloud AI services (Azure OpenAI, Google Cloud AI, etc.), enterprise automation tools (Airtable, Softr), and multi-cloud AI deployments.
Develop and fine-tune AI models using cloud-based services such as Azure OpenAI, Google Cloud AI, and OpenAI API.
Optimize AI pipelines for scalability and efficiency in cloud-hosted environments.
Ensure cross-platform AI compatibility, allowing seamless switching between different model providers.
Design and implement AI-driven enterprise automation workflows integrating AI models, databases, and API-driven tools.
Configure and optimize retrieval-augmented generation (RAG) workflows, including vector database management and AI-powered data retrieval.
Develop and manage utility interfaces using no-code/low-code platforms such as Airtable and Softr.
Deploy AI models and automation workflows in enterprise environments, ensuring smooth integration and performance.
2 - 3 years of experience in AI/ML development, enterprise automation, or AI model engineering.
Proficiency in cloud-based AI services (Azure OpenAI, Google Cloud AI, OpenAI API).
Strong understanding of AI fine-tuning, model training, and data preprocessing techniques.
Experience integrating AI models with structured automation workflows.
Hands-on experience with RAG workflows, vector databases, and AI-powered retrieval.
Proficiency in API integration and SDKs for deploying AI models into production.
Experience with no-code/low-code tools like Airtable, Softr, or similar platforms.
Knowledge of data security, compliance, and best practices for AI deployment.
Fluent in English
Experience with multi-cloud AI deployments and switching between AI providers.
Knowledge of on-prem and edge AI deployments.
Expertise in DevOps/MLOps, including CI/CD pipelines, Docker, and Kubernetes.
Familiarity with logging, monitoring, and observability tools for AI automation.
Strong communication skills and ability to work with enterprise clients.
Experience with N8N.
Competitive salary in USD.
15 days PTO
Flexible working hours
Remote Work.
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